Data from Functional Interplay of p53 and Mus81 in DNA Damage Responses and Cancer
Bibliographic record
Abstract
Abstract Mus81 plays an integral role in the maintenance of genome stability and DNA repair in mammalian cells. Deficiency of Mus81 in human and mouse cells results in hypersensitivity to interstrand cross-linking (ICL) agents and elevated levels of genomic instability. Furthermore, Mus81-mutant mice are susceptible to spontaneous lymphomas. The role of cellular checkpoints in mediating the phenotypes observed in Mus81-deficient cells and mice is currently unknown. In this study, we have observed increased activation of p53 in Mus81−/− cells in response to ICL-induced DNA damage. In addition, p53 inactivation completely rescued the ICL hypersensitivity of Mus81−/− cells, signifying p53 is essential for the elimination of ICL-damaged cells in the absence of Mus81. Confirming that p53 acts as a critical checkpoint for the Mus81 repair pathway, a synergistic increase of spontaneous and ICL-induced genomic instability was observed in Mus81−/−p53−/− cells. To clarify the genetic interactions of Mus81 and p53 in tumor suppression, we monitored Mus81−/−p53−/− and control mice for the development of spontaneous tumors. Significantly, we show that loss of even a single allele of Mus81 drastically modifies the tumor spectrum of p53-mutant mice and increases their predisposition to developing sarcomas. Our results reveal a key role for p53 in mediating the response to spontaneous and ICL-induced DNA damage that occurs in the absence of Mus81. Furthermore, our data show that loss of Mus81, in addition to p53, is a key step in sarcoma development. [Cancer Res 2007;67(18):8527–35]
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".